ADP덤프문제최신버전시험기출문제

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Google ADP Exam Syllabus Topics:

Section	Weight	Objectives
Data Analysis and Presentation	27%	- Data visualization 1. Looker / Looker Studio reporting - Querying and analyzing data 1. BigQuery SQL usage 2. Data aggregation and transformation
Data Preparation and Ingestion	30%	- Data ingestion into Google Cloud services 1. Streaming ingestion with Pub/Sub concepts 2. Cloud Storage ingestion patterns
Data Pipeline Orchestration	18%	- Pipeline design and automation 1. Dataflow pipelines 2. Workflow orchestration concepts (e.g., Cloud Composer)
Data Management	25%	- Storage and data organization 1. BigQuery datasets and tables management 2. Cloud Storage lifecycle policies - Data governance and security 1. Data lifecycle management 2. IAM and access control

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ADP덤프문제 최신 업데이트된 덤프공부자료

아무런 노력을 하지 않고 승진이나 연봉인상을 꿈꾸고 있는 분이라면 이 글을 검색해낼수 없었을것입니다. 승진이나 연봉인상을 꿈꾸면 승진과 연봉인상을 시켜주는 회사에 능력을 과시해야 합니다. IT인증시험은 국제적으로 승인해주는 자격증을 취득하는 시험입니다. KoreaDumps의Google인증 ADP덤프의 도움으로 Google인증 ADP시험을 패스하여 자격증을 취득하면 승진이나 연봉인상의 꿈이 이루어집니다. 결코 꿈은 이루어질것입니다.

최신 Google Cloud Certified ADP 무료샘플문제 (Q40-Q45):

질문 # 40
Your organization's ecommerce website collects user activity logs using a Pub/Sub topic. Your organization's leadership team wants a dashboard that contains aggregated user engagement metrics. You need to create a solution that transforms the user activity logs into aggregated metrics, while ensuring that the raw data can be easily queried. What should you do?

A. Create a BigQuery subscription to the Pub/Sub topic, and load the activity logs into the table. Create a materialized view in BigQuery using SQL to transform the data for reporting
B. Create a Dataflow subscription to the Pub/Sub topic, and transform the activity logs. Load the transformed data into a BigQuery table for reporting.
C. Create an event-driven Cloud Run function to trigger a data transformation pipeline to run. Load the transformed activity logs into a BigQuery table for reporting.
D. Create a Cloud Storage subscription to the Pub/Sub topic. Load the activity logs into a bucket using the Avro file format. Use Dataflow to transform the data, and load it into a BigQuery table for reporting.

정답：B

질문 # 41
Your company uses Looker as its primary business intelligence platform. You want to use LookML to visualize the profit margin for each of your company's products in your Looker Explores and dashboards.
You need to implement a solution quickly and efficiently. What should you do?

A. Create a derived table that pre-calculates the profit margin for each product, and include it in the Looker model.
B. Create a new dimension that categorizes products based on their profit margin ranges (e.g., high, medium, low).
C. Define a new measure that calculates the profit margin by using the existing revenue and cost fields.
D. Apply a filter to only show products with a positive profit margin.

정답：C

질문 # 42
Your retail company wants to analyze customer reviews to understand sentiment and identify areas for improvement. Your company has a large dataset of customer feedback text stored in BigQuery that includes diverse language patterns, emojis, and slang. You want to build a solution to classify customer sentiment from the feedback text. What should you do?

A. Use Dataproc to create a Spark cluster, perform text preprocessing using Spark NLP, and build a sentiment analysis model with Spark MLlib.
B. Develop a custom sentiment analysis model using TensorFlow. Deploy it on a Compute Engine instance.
C. Preprocess the text data in BigQuery using SQL functions. Export the processed data to AutoML Natural Language for model training and deployment.
D. Export the raw data from BigQuery. Use AutoML Natural Language to train a custom sentiment analysis model.

정답：D

질문 # 43
Your organization has a petabyte of application logs stored as Parquet files in Cloud Storage. You need to quickly perform a one- time SQL-based analysis of the files and join them to data that already resides in BigQuery. What should you do?

A. Create a Dataproc cluster, and write a PySpark job to join the data from BigQuery to the files in Cloud Storage.
B. Launch a Cloud Data Fusion environment, use plugins to connect to BigQuery and Cloud Storage, and use the SQL join operation to analyze the data.
C. Create external tables over the files in Cloud Storage, and perform SQL joins to tables in BigQuery to analyze the data.
D. Use the bq load command to load the Parquet files into BigQuery, and perform SQL joins to analyze the data.

정답：C

질문 # 44
You are working with a small dataset in Cloud Storage that needs to be transformed and loaded into BigQuery for analysis. The transformation involves simple filtering and aggregation operations. You want to use the most efficient and cost-effective data manipulation approach. What should you do?

A. Use Dataflow to perform the ETL process that reads the data from Cloud Storage, transforms it using Apache Beam, and writes the results to BigQuery.
B. Use BigQuery's SQL capabilities to load the data from Cloud Storage, transform it, and store the results in a new BigQuery table.
C. Create a Cloud Data Fusion instance and visually design an ETL pipeline that reads data from Cloud Storage, transforms it using built-in transformations, and loads the results into BigQuery.
D. Use Dataproc to create an Apache Hadoop cluster, perform the ETL process using Apache Spark, and load the results into BigQuery.

정답：B

질문 # 45
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